Surgical palliation of hypoplastic left heart syndrome: is there a role for hypothermic circulatory arrest?
Bibliographic record
Abstract
The technique of deep hypothermia with circulatory arrest has been important in the history of the evolution of cardiac surgery. Wilfred G. Bigelow, working in Toronto in the late 1940s, performed pioneering research on hypothermia, and developed a workable technique of hypothermia in human cardiac surgery.1Based upon Bigelow's experimental premises, F. John Lewis, at the University of Minnesota, also conducted a number of experiments utilizing hypothermia. On September 2, 1942, Lewis operated on a 5-year-old girl with an atrial septal defect under general hypothermia with inflow occlusion. He was assisted by Richard Varco, Mansur Taufic, and C. Walton Lillehei. Rubberized refrigerated blankets were used to cool the patient to 28°C. The septal defect was closed during five and a half minutes of inflow occlusion. This was the world's first successful open operation on the human heart performed under direct vision, and marked the beginning of the era of open heart surgery. Now, as amazing and as primitive as that methodology may seem, those of you who read Life magazine, or watch the Discovery Channel on television, are aware that, in parts of the Soviet Union, a large fraction of today's open heart surgery is performed not using the technique of cardiopulmonary bypass, but rather using the methodology of immersion hypothermia from the 1950s, with surprisingly good results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".